Thermal modeling and parameter identification of lithium battery in energy storage system

Lithium ion batteries are widely used in energy storage systems because of their fast response, high energy density and other characteristics. However, during the charging and discharging process of lithium battery, the internal chemical reaction rate is accelerated, and more heat is generated, resulting in the rapid rise of battery temperature, which affects the safety of the battery. In order to effectively solve the overheating problem of lithium-ion battery in the process of charging and discharging, and ensure the safety and performance stability of the battery, the lumped parameter thermal model of 280 Ah lithium iron phosphate battery was established, and the temperature distribution and its change law in the battery were analyzed. The adaptive weighted particle swarm optimization (AWPSO) algorithm was used to identify the parameters of the thermal model to improve the accuracy of the model. The battery thermal model was built in Matlab/Simulink, and the temperature error was 0.6 °C through the comparison of simulation experiments, which provided theoretical basis and technical support for the battery thermal management system.